EP2796899A2 - Seismische Datenverarbeitung und Vorrichtung - Google Patents

Seismische Datenverarbeitung und Vorrichtung Download PDF

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Publication number
EP2796899A2
EP2796899A2 EP14162550.9A EP14162550A EP2796899A2 EP 2796899 A2 EP2796899 A2 EP 2796899A2 EP 14162550 A EP14162550 A EP 14162550A EP 2796899 A2 EP2796899 A2 EP 2796899A2
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EP
European Patent Office
Prior art keywords
facets
velocity model
seismic data
time
migrated
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP14162550.9A
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English (en)
French (fr)
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EP2796899A3 (de
Inventor
Gilles Lambare
Jean-Paul Toure
Ziqin Yu
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Sercel SAS
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CGG Services SAS
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Priority claimed from US13/868,422 external-priority patent/US9348048B2/en
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Publication of EP2796899A2 publication Critical patent/EP2796899A2/de
Publication of EP2796899A3 publication Critical patent/EP2796899A3/de
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/303—Analysis for determining velocity profiles or travel times
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/50—Corrections or adjustments related to wave propagation
    • G01V2210/51—Migration

Definitions

  • This invention relates to the field of seismic imaging. More specifically, it relates to a method of seismic data processing.
  • acoustic transmitters placed, for example, at the surface.
  • the transmitters S also called sources
  • the acoustic waves reflected toward the surface are recorded as a function of time by receivers R.
  • the signals recorded by the receivers are called seismic traces.
  • Various digital processing techniques are conventionally applied to these traces so as to improve the signal-to-noise ratio and facilitate their interpretation.
  • These techniques include the migration operation, which consists of determining, for a plurality of surface positions P of coordinates (x, y), a collection of migrated traces bearing information on events that describe the subsurface in line with the surface position P (x, y).
  • the migration can be applied before or after the stacking of the traces, and we refer to time migration or depth migration depending on whether the output traces are represented according to the time or the depth.
  • the repositioning of events is based on a model of the wave propagation velocity in the subsurface, i.e., a time-velocity model for the time migration or a depth-velocity model for the depth migration.
  • the time- or depth-velocity model makes it possible to calculate the travel time between the source and receiver positions and the image point.
  • the estimation of the time- or depth-velocity model is an important and difficult step in the seismic processing chain.
  • CIP Common Image Point
  • these CIP gathers are organized according to the source-receiver distance (also called the offset distance) as shown in FIG. 2 , but it is also possible to organize them according to the angles of reflection, the orientation of the source-receiver segment, slopes at the surface, the position of the sources and receivers, etc.
  • the analysis of the migrated images obtained for these different classes is the basis for numerous seismic trace processing techniques.
  • CIP gathers are very widely used for the interpretation of subterranean geological structures:
  • a method of seismic data processing includes receiving seismic data that includes a set of seismic traces, each trace including a signal recorded by a sensor after having been propagated in a subsurface area; migrating the seismic data according to a first velocity model; picking from the time-migrated seismic data one or more events corresponding to one or more subsurface reflectors so as to obtain a set of facets locally approximating the event; kinematic demigrating the picked set of facets so as to obtain simplified seismic data that includes the set of facets and a set of attributes associated with the set of facets; kinematic migrating the set of facets based on a second velocity model; and updating the initial velocity model based on an alignment of migrated points within the set of facets.
  • the computing device includes an interface configured to receive seismic data that includes a set of seismic traces, each trace including a signal recorded by a sensor after having been propagated in a subsurface area; and a processor connected to the interface.
  • the processor is configured to migrate the seismic data according to a first velocity model, pick from the time-migrated seismic data one or more events corresponding to one or more subsurface reflectors so as to obtain a set of facets locally approximating the event, kinematic demigrate the picked set of facets so as to obtain simplified seismic data that includes the set of facets and a set of attributes associated with the set of facets, kinematic migrate the set of facets based on a second velocity model, and update the initial velocity model based on an alignment of migrated points within the set of facets.
  • the method includes a step of receiving seismic data that includes a set of seismic traces. Each trace includes a signal recorded by a sensor after having propagated in an area of the subsurface, with the signal being defined by amplitude as a function of time.
  • the method also includes a step of migration of the seismic data according to an initial time-velocity model, a step of picking in the time-migrated seismic data one or more events corresponding to one or more reflectors of the subsurface so as to obtain facets locally approximating the event, and a step of kinematic demigration of the facets plotted so as to obtain simplified seismic data in the form of a set of facets and a set of attributes associated with the facets.
  • face refers to a close local representation of an event on a neighboring area of traces, migrated or not, which representation is defined by attributes locally characterizing the event.
  • the attributes is associated with a central position of the event and local slopes of the event in the gather of traces.
  • the kinematic demigration step is performed on the basis of the same initial time-velocity model as the time migration step.
  • the invariant attributes include, for example, for each facet after demigration, a time of a reflected event, source and receiver positions, and local slopes of the event reflected in the gather of traces.
  • the demigrated facets correspond to the local events that can be observed on the gathers of non-migrated traces, and are not dependent upon the velocity model used for the time-migration and time-demigration steps.
  • kinematic demigration The demigration of facets is called “kinematic demigration" because it is applied only to the kinematic characteristics of the reflected field and not to the associated wavelets. In one embodiment, it is possible to take advantage of pre-stack time-migrated data from a previous processing operation.
  • the processing method is applied to this pre-stack time-migrated data, it does not require a step of building an initial depth model or a step of pre-stack depth migration (pre-SDM).
  • pre-SDM pre-stack depth migration
  • the step of picking data is facilitated by the quality of the pre-stack time-migrated data, without compromising the quality of the kinematic information recovered from the facets.
  • the kinematic invariants obtained by this process can then be used in a seismic data tomographic inversion process.
  • An iterative process is, for example, described in document EP1239304 , which does not require, at each non-linear iteration, picking and pre-stack migration of the initial seismic data.
  • the attributes associated with the facets include, in addition to the attributes representative of kinematic invariants (times, source and receiver positions, slopes in the non-migrated domain), a specular reflection angle, phase angles, an instantaneous velocity, a vertical stretch factor, a depth dip, CRS (Common Reflection Surface) attributes, or a time shift of a ghost.
  • the seismic data processing process shown in FIGS. 3 and 4 includes two processing phases: a first phase 100 of generating the kinematic invariants ( FIG. 3 ) and a second phase 200 of tomographic inversion of these kinematic invariants, i.e., an estimation of the time- or depth-velocity model ( FIG. 4 ), based on the kinematic invariants.
  • the first phase of the processing algorithm which is shown in FIG. 3 , is applied to time traces before migration. These traces correspond to the recording, as a function of time, by a sensor, of the amplitude of the signal propagated underground (e.g., pressure recorded by a hydrophone).
  • a migration of these seismic traces is performed according to an initial time-velocity model (PreSTM).
  • PreSTM initial time-velocity model
  • a second step 102 on each gather of traces obtained in the previous step, one or more events reflected in line with the surface point considered are picked.
  • FIG. 5 diagrammatically shows a cross-section of the pre-stack time-migrated seismic data (PreSTM) stacked on the CIP gathers (at the left) and common image point (CIP) gathers (at the right) from this data.
  • the position of the CIP gathers is indicated in the cross-section by a dotted line.
  • RMO curves, which characterize the alignment of the data picked in the CIP gathers have been superimposed with the picked data.
  • a time and the associated time-migrated facet are determined.
  • the facet may be characterized by a dip (in directions x, y) and possibly a slope in the direction of the CIP gathers.
  • a fourth step 104 the kinematic demigration of the migrated facet is performed.
  • Kinematic demigration is a process that transforms one facet (i.e., an image) back to the seismic data. This step may be repeated until more than one facet are kinematically demigrated.
  • the facet is characterized by source and receiver positions, by a central time and by slopes, taking into consideration the acquisition geometry and the rules of focusing on the times and the time migration gradients described, for example, in Chauris et al., 2001 a, Migration velocity analysis from locally coherent events in 2-D laterally heterogeneous media, Part I: Theoretical aspects, Geophysics, Vol. 67, No.
  • the calculation of the acoustic source-receiver pair is a well-known step that can be performed according to a plurality of established techniques. Based on the acoustic source-receiver pair, various attributes associated with the plotted event are also determined in step 105 for each facet, such as the angles of reflection, the phase angles, the instantaneous velocity, the stretch factor, the depth dip, the time shift of the ghost and optionally the CRS attributes. For all of these operations, the basic data are the components of the gradient of the time-migration time.
  • demigrated attributes make it possible to characterize local events that can be observed in the seismic traces before migration. As their characteristic does not depend upon the velocity model used for the migration, these data are referred to as kinematic invariants.
  • the components of the time migration gradients makes it possible to calculate a stretch factor, a specular reflection angle, phase angles, an instantaneous velocity, a depth dip, CRS attributes, and the time shift of the ghost, an attribute for computing the time shift in the migration panel when the depth of the recording surface changes.
  • the calculation of the specular reflection angle ⁇ associated with the offset-ordered common image point collections is obtained by considering the local dip of the event (assumed to be an offset invariant), and by comparing the values of the "vertical" component of the gradient of the double time of time-migration at various offsets ( FIG. 11 ). Indeed, the ratio of this component of the gradient at a given offset with that with a zero offset gives the cosine of the specular reflection angle. It should be noted that the calculation can also be performed for CIP gathers arranged in shot position or in source or receiver position.
  • T SR is the double time of the time-migration operator
  • t 0 is the time of the time-migrated image.
  • the calculation of an instantaneous velocity V inst on the basis of horizontal and vertical components of the gradient of the one-way travel time of time-migration is obtained by expressing this vector using the angle of incidence of the wave and the instantaneous velocity ( FIG. 12 ).
  • the calculation can be performed for all of the source and receiver geometries, which makes it possible to access anisotropic parameters using the information on the phase angle and the dip estimated below.
  • the instantaneous velocity is given by: v inst .
  • T 1 - / ⁇ t 0 ⁇ T 2 / ⁇ x ⁇ T , where T is the one-way travel time of the time-migration operator (for the source or receiver path), x is the horizontal position in the image, and t 0 is the time of the time-migrated image.
  • z the depth of the event observed in the depth-migrated
  • x the horizontal position in the image
  • CRS attributes The estimation of CRS attributes is obtained by adjustment on the distribution of kinematic invariants obtained by time-demigration of local curve events. These CRS attributes can be used to estimate a depth-velocity model, or for various other applications of the CRS attributes.
  • Another attribute that may be introduced is a time shift of the ghost.
  • This attribute can be used for estimating the signal of the ghost, i.e., for computing the time shift in the migration panel when the depth of the recording surface changes (because of sources and/or receivers).
  • This attribute can also be generalized to perform data redatuming after migration. For example, this attribute can be estimated in a similar way as locally coherent events picked on prestack depth migrated seismic data.
  • FIGS. 8 to 14 diagrammatically show a two-dimensional case, the process can be generalized, as will be recognized by those skilled in the art, directly to a three-dimensional case.
  • FIG. 9 diagrammatically shows a focusing condition of the kinematic time migration. For a given dip, the position of the migrated point (x, to) and those of the source and the receiver will satisfy this condition.
  • FIG. 10 diagrammatically shows a step of determining the vertical stretch.
  • FIG. 11 diagrammatically shows a step of determining the cosine of the reflection angle.
  • the ratio between the vertical stretch values with a given offset and that with a zero offset is determined. This estimation assumes an isotropic medium.
  • FIG. 12 diagrammatically shows a step of determining the instantaneous velocity.
  • the components of the single, source or receiver transit time gradients are used. The velocity can therefore be obtained for the source and receiver trajectories.
  • FIG. 13 diagrammatically shows a step of determining the depth dip on the basis of the time dip and the instantaneous velocity.
  • FIG. 14 diagrammatically shows a step of determining phase angles. Slowness vectors are calculated from instantaneous velocities and are used to derive phase angles, in particular reflection phase angles.
  • FIG. 15 diagrammatically shows a step of determining the time shift of the ghost.
  • the second phase 200 of the processing process shown in FIG. 4 is applied to the kinematic invariants discussed above.
  • a processing operation is implemented, making it possible to estimate a time-velocity or a depth-velocity model according to which the following steps are iterated.
  • a kinematic migration (time or depth) of the kinematic invariants obtained above is performed using a model of the velocity field (time or depth) of the subsurface.
  • an alignment of the obtained migrated points is characterized.
  • the migrated points may be, for example, center of the facets. If the migrated points are the center of the facets, the alignment compares their positions, and/or the local dips, and/or slopes or other parameters. French Patent FR 2 821 677 describes such alignment measurements. It is also possible to apply a criterion for minimizing the slope of the migrated events in the CIP gathers (Chauris et al., 2001 a).
  • Step 203 includes a step of selecting a time- or depth-velocity field setting of parameters that optimizes the alignment of the migrated facets. In other words, new settings for the parameters are determined so that the alignment of the migrated points is improved. These parameters are then used to update the velocity model.
  • Steps 201, 202 and 203 can be repeated until an alignment deemed to be sufficient is obtained.
  • FIG. 6 diagrammatically shows an example of pre-stack depth-migrated CIP gathers (PreSDM) obtained by respectively applying the final velocity model obtained using a picking in the pre-stack time-migrated data (above) and the final velocity model obtained by using a picking in the pre-stack depth-migrated data (below).
  • PreSDM pre-stack depth-migrated CIP gathers
  • FIG. 7 diagrammatically shows an initial depth-velocity model (at left) and a final depth-velocity model (at right) obtained in the second phase of the process.
  • a method of seismic data processing that includes a step 1600 of receiving seismic data that includes a set of seismic traces, each trace including a signal recorded by a sensor after having been propagated in a subsurface area; a step 1602 of migrating the seismic data according to a first velocity model; a step 1604 of picking from the time-migrated seismic data one or more events corresponding to one or more subsurface reflectors so as to obtain a set of facets locally approximating the event; a step 1606 of kinematic demigrating the picked set of facets so as to obtain simplified seismic data that includes the set of facets and a set of attributes associated with the set of facets; a step 1608 of migrating the set of facets based on a second velocity model; and a step 1610 of updating the initial velocity model based on an alignment of migrated points within the set of facets.
  • Such a computing device 1700 includes a processor 1702 and a storage device 1704 that communicate with each other via a bus 1706.
  • An input/output interface 1708 also communicates with the bus 1706 and allows an operator to communicate with the processor or the memory, for example, to input software instructions for calculating one or more of the attributes.
  • Computing device 1700 may be a computer, a server, a processor or dedicated circuitry.

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EP14162550.9A 2013-04-23 2014-03-31 Seismische Datenverarbeitung und Vorrichtung Withdrawn EP2796899A3 (de)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108333628A (zh) * 2018-01-17 2018-07-27 中国石油大学(华东) 基于正则化约束的弹性波最小二乘逆时偏移方法
CN111596360A (zh) * 2019-02-21 2020-08-28 中国石油天然气集团有限公司 一种提高三维初至层析反演精度的方法及装置

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2821677A1 (fr) 2001-03-05 2002-09-06 Geophysique Cie Gle Perfectionnements aux procedes d'inversion tomographique d'evenements pointes sur les donnees sismiques migrees

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FR2878966B1 (fr) * 2004-12-07 2007-02-09 Inst Francais Du Petrole Methode pour determiner des informations speculaires apres imagerie sismique avant sommation
FR2916859B1 (fr) * 2007-05-31 2009-08-21 Cgg Services Sa Procede de traitement de donnees sismiques
FR2976088B1 (fr) * 2011-05-30 2014-03-07 Cggveritas Services Sa Procede de tomographie non lineaire pour un axe de symetrie principal d'un modele de vitesse anisotrope et dispositif

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2821677A1 (fr) 2001-03-05 2002-09-06 Geophysique Cie Gle Perfectionnements aux procedes d'inversion tomographique d'evenements pointes sur les donnees sismiques migrees
EP1239304A1 (de) 2001-03-05 2002-09-11 Compagnie Generale De Geophysique Verbesserungen an Verfahren zur tomographischen Invertierung von ausgewählten Ereignissen in migrierten seismischen Daten

Non-Patent Citations (4)

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Title
CHAURIS ET AL.: "Migration velocity analysis from locally coherent events in 2-D laterally heterogeneous media", THEORETICAL ASPECTS, GEOPHYSICS, vol. 67, no. 4, 2001, pages 1202 - 1212
CHAURIS ET AL.: "Migration velocity analysis from locally coherent events in 2-D laterally heterogeneous media, Part II: Applications on synthetic and real data", GEOPHYSICS, vol. 67, no. 4, 2001, pages 1213 - 1224
GUILLAUME ET AL.: "3D Finite-offset tomographic inversion of CRP-scan data, with or without anisotropy, 71.sup.st annual SEG meeting", EXP. ABSTRACTS, 2001
GUILLAUME ET AL.: "Flexible 3D finite-offset tomography velocity model building", EAGE, 2004

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108333628A (zh) * 2018-01-17 2018-07-27 中国石油大学(华东) 基于正则化约束的弹性波最小二乘逆时偏移方法
CN111596360A (zh) * 2019-02-21 2020-08-28 中国石油天然气集团有限公司 一种提高三维初至层析反演精度的方法及装置
CN111596360B (zh) * 2019-02-21 2023-09-26 中国石油天然气集团有限公司 一种提高三维初至层析反演精度的方法及装置

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